p <- df %>% 
  select(run_number = .run.number., chance_imp = importance.of.chance, 
         step = .step., contains("gini")) %>% 
  pivot_longer(contains("gini")) %>% 
  mutate(chance_imp = factor(chance_imp, labels = chance_imp %>% unique() %>%
                               as.numeric() %>% scales::percent())) %>%
  ggplot(aes(step, value, colour = factor(chance_imp))) +
  geom_smooth() +
  facet_wrap(vars(name)) +
  labs(y = "gini", 
       colour = "importance of chance",
       caption = "n = 100 agents") 
p
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

plotly::ggplotly(p)
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'